A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns

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Title: A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns
Authors: Cradden, Lucy C.McDermott, FrankZubiate, LauraSweeney, ConorO'Malley, Mark
Permanent link: http://hdl.handle.net/10197/8402
Date: Jun-2017
Abstract: To study climate-related aspects of power system operation with large volumes of wind generation, data with sufficiently wide temporal and spatial scope are required. The relative youth of the wind industry means that long-term data from real systems are not available. Here, a detailed aggregated wind power generation model is developed for the Republic of Ireland using MERRA reanalysis wind speed data and verified against measured wind production data for the period 2001–2014. The model is most successful in representing aggregate power output in the middle years of this period, after the total installed capacity had reached around 500 MW. Variability on scales of greater than 6 h is captured well by the model; one additional higher resolution wind dataset was found to improve the representation of higher frequency variability. Finally, the model is used to hindcast hypothetical aggregate wind production over the 34-year period 1980–2013, based on existing installed wind capacity. A relationship is found between several of the production characteristics, including capacity factor, ramping and persistence, and two large-scale atmospheric patterns – the North Atlantic Oscillation and the East Atlantic Pattern.
Funding Details: Science Foundation Ireland
University College Dublin
Funding Details: Marie Skłodowska-Curie FP7-PEOPLE-2013-COFUND
Type of material: Journal Article
Publisher: Elsevier
Journal: Renewable Energy
Volume: 106
Start page: 165
End page: 176
Copyright (published version): 2017 Elsevier
Keywords: Wind powerMERRA reanalysisNorth Atlantic OscillationEast Atlantic Pattern
DOI: 10.1016/j.renene.2016.12.079
Language: en
Status of Item: Peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Earth Sciences Research Collection
Mathematics and Statistics Research Collection
Electrical and Electronic Engineering Research Collection
Energy Institute Research Collection
Climate Change Collection

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